Despite the large bandwidth available for all users in high-speed wireless networks, resources allocation and user scheduling remain essential to combat interference, increase throughput and reduce complexity. As the number of users increases, the computational complexity tends to increase significantly. The trade-off between the complexity reduction and capacity improvement is the challenge. Henc...
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Power line interference (PLI) corrupts biomedical recordings. A notch filter is one of the filters that has been suggested to suppress the fundamental PLI and its harmonics in electrocardiographic recordings. Using finite impulse response (FIR) filters are one of the interesting ways to filter this interference in order to receive a rather pure signal. The frequent use of FIR filters create a fiel...
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This paper focuses on one of the key enabling technology that will compose future 5G network, the Direct-LTE communication underlying a cellular infrastructure, also commonly known as Device-to-Device (D2D). Energy efficiency algorithms are proposed for the communication between D2D users and cellular users (CUs) and, following the Lagrangian duality theory, an optimal power and rate control solut...
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The mixed l2/lp (0 <; p ≤ 1) norm minimisation method with partially known support for recovering block-sparse signals is studied. The authors mainly extend this work on block-sparse compressed sensing by incorporating some known part of the block support information as a priori and establish sufficient restricted p-isometry property (...
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In this study, the performance of the likelihood-based digital modulation classification is explored with the blind estimation of the unknown parameters. Considering the practical implementation aspects, the quasi hybrid likelihood ratio test (QHLRT) is examined with the symbol rate, the signal gain, the noise power and the phase offset as the unknown parameters. In a blind scenario, new algorithm...
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Blind image deblurring is an important topic which is widely used in many research fields such as photography, optics, astronomy, medical images, monitoring, military and so on. Although many algorithms have been proposed to improve the deblurring result in the past years, most of them cannot perform perfectly in some challenging cases. This study presents a novel blind deblurring method based on ...
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Electrocardiogram (ECG) beat behaves as a non-linear and non-stationary signal. Since most of the existing data processing tools are poor alternatives for processing such signals, Hilbert-Huang transform (HHT) proves to be an efficient method as it deals with a time-varying frequency spectrum. In this study, a new and efficient methodology is proposed using HHT for feature selection which includes...
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Snore related signals (SRS) have been found to carry important information about the snore source and obstruction site in the upper airway of an Obstructive Sleep Apnea/Hypopnea Syndrome (OSAHS) patient. An overnight audio recording of an individual subject is the preliminary and essential material for further study and diagnosis. Automatic detection, segmentation and classification of SRS from ov...
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The measurement of optical fibre vibration is a key part of optic fibre pre-warning system, which has gradually focused on phase-sensitive optical time-domain reflectometer. However, for this instrument, false alarm rate is very high and some unstable intrusion signals cannot be detected by using its fixed threshold method in the actual application. It needs to develop new vibration detection meth...
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The authors propose entropy minimisation-based matching pursuit algorithm which has the capability to reject noise even when the noise level is comparable to the signal level. The proposed algorithm can cater to compressible signals and sparse signals with unknown sparsity.
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Compressive sensing (CS) provides a new paradigm of sub-Nyquist sampling which can be considered as an alternative to Nyquist sampling theorem. In particular, providing that signals are with sparse representations in some domain, information can be perfectly preserved even with small amount of measurements captured by random projections. Besides sparsity prior of signals, the inherent structure pr...
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With the wide spread availability and the favourable Doppler resolution, the frequency modulation (FM) commercial radio signals have become attractive for passive radar applications. Passive radar networks using multiple illuminators of opportunity and multichannel receivers have been shown to offer significant performance improvement owing to their advantage of signal and spatial diversities. In ...
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In this study, the authors discuss relay selection schemes with the objective to minimise outage probability for a network consisting of a single source, multiple relays and a single destination. The relays are powered by radio frequency signals from the source. For a successful transmission, at least one of the relay nodes should be able to decode the source signals and have enough energy to rela...
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This paper describes how modern field programmable gate array (FPGA) technology can be used to build practical and efficient multiplicative finite impulse response (MFIR) filters with low-pass, high-pass, band-pass and band-stop characteristics. This paper explains how MFIR structures can be built with or without linear phase characteristics and implemented efficiently on modern FPGA architectures...
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This study addresses the problem of tracking extended target with intermittent observations. Based on practical applications, two Bernoulli distributed random variables are employed to describe the intermittent phenomenon of the positional measurements and the measurements of target extent, respectively. First, a machine vision algorithm is developed to solve the target shape parameters. Then, fou...
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An anti-jamming model is set up for the high dynamic global positioning system (GPS) receiver embedded in a high-speed vehicle. With a view to identify the characteristics of interferences in high dynamic condition and the shortcomings of traditional null widening methods, a novel statistical space-time null widening (SSTNW) method is proposed in this study. The SSTNW method can suppress interfere...
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The fusion estimation problem for a class of multi-sensor asynchronous sampling linear stochastic systems with missing measurements is considered, where the state is updated uniformly and each sensor non-uniformly samples one measurement at most within a state update period. Based on the sampled measurement data of each sensor, the optimal local state estimators are designed at the state and measu...
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Polyphase codes including Frank, P1, P2, P3 and P4 codes are different from linear frequency modulation (LFM) and conventional phase coding, which have brought great challenges to current reconnaissance systems. Polyphase codes are derived from approximation to LFM waveforms. By theoretical derivation and simulation analysis, the authors can conclude that time-frequency rate (TFR) distribution is ...
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The harmonic parameter identification and modelling problem for power signals are studied. In order to model power signals, the multi-innovation stochastic gradient (MI-SG) is derived based on the multi-innovation identification theory. The proposed MI-SG algorithm repeatedly uses past innovations by expanding the scalar innovation to the innovation vector and can obtain more accurate parameter es...
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This paper considers the secure communication issue in an amplify-and-forward relaying cooperative network, in which the energy harvesting relay is powered by radio-frequency signals from the source. Based on the two different energy harvesting strategies, that is, power splitting-based relaying protocols and time switching-based relaying protocols, the authors formulate the problem for maximising...
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This paper presents an algorithm for estimating the instantaneous fundamental frequency of a noisy non-stationary periodic signal whose components are harmonically related. To this end, the authors' propose a harmonic state-space model for the input signal and use it to derive an extended Kalman filter (EKF), an unscented Kalman filter (UKF) and a particle filter (PF). In this model, the input sig...
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Adaptive notch filters have been the focus of intense research for more than three decades. Low computational requirements and good performance make them attractive for tracking frequency modulated signals. Despite the extensive literature on adaptive notch filters, algorithm extensions and new models for describing the dynamics of the notch frequency continue to be proposed. In this study, the eq...
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State-of-the-art speech representations provide acceptable recognition results under optimal conditions, though their performance in adverse conditions still needs to be improved. In this direction, many advances involving wavelet processing have been reported, showing significant improvements in classification performance for different kinds of signals. However, for speech signals, the problem of...
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In this study, the authors propose a lattice reduction (LR)-based doubly iterative receiver for joint channel estimation and detection in multiple-input-multiple-output (MIMO) bit-interleaved coded modulation systems. For the inner iteration loop of the receiver, LR-based randomised sampling detection is employed to enjoy the tradeoff between performance and complexity while for the outer iteratio...
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This study proposes an optimised algorithm to remove power line interference (PLI) from electrocardiogram (ECG) signal based on ensemble empirical mode decomposition (EEMD). A computationally efficient algorithm is one of the important requirements for real-time monitoring of cardio activities and diagnosis of arrhythmias. Computational complexity in EEMD is significantly reduced by using the EMD ...
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Electrocardiogram (ECG) signals are usually corrupted by baseline wander, power-line interference, muscle noise etc. Numerous methods have been proposed to remove these noises. However, in case of wireless recording of the ECG signal it gets corrupted by the additive white Gaussian noise (AWGN). For the correct diagnosis, removal of AWGN from ECG signals becomes necessary as it affects the diagnos...
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This study proposes low-complexity robust adaptive beamforming (RAB) techniques based on shrinkage methods. The authors first review a low-complexity shrinkage-based mismatch estimation batch algorithm to estimate the desired signal steering vector mismatch, in which the interference-plus-noise covariance matrix is also estimated by a recursive matrix shrinkage method. Then they develop low-comple...
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This study presents a speech filtering method exploiting the combined effects of the empirical mode decomposition (EMD) and the local statistics of the speech signal using the adaptive centre weighted average (ACWA) filter. The novelty lies in incorporating the frame class (voiced/unvoiced) in the conventional filtering using the EMD and the ACWA filter. The speech signal is segmented into frames ...
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In this study, the authors investigate the impact of channel estimation error (CEE) on the performance of a multiple-input-multiple-output (MIMO) two-way relay system under Rayleigh fading. Herein, transmit/receive zero-forcing (ZF) is employed at the two source nodes, whereas analogue network coding is used at the relay node. Fundamentally, for making use of transmit/receive ZF, all nodes must be...
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Digital active noise control (ANC) for headphones usually has to predict the noise because of the latency of common audio converters. In adaptive feedback ANC, the prediction is based on the noise that entered the headphone. This noise is low-pass filtered because of the physical barrier of the ear cups. In this study, this low-pass characteristic is exploited to define a prediction filter which d...
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In the state-of-the-art single channel speech enhancement techniques, the short-time spectral amplitude is modified while the effect of the phase corruption due to the contamination of additive noise is neglected. This study introduces an improved speech enhancement algorithm based on a phase-aware multi-band spectral subtraction technique which estimates the spectral amplitude of the clean speech...
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Sparse modelling with the ℓp norm of 0 ≤ p ≤ 1 requires the availability of the proximity operator of the ℓp norm. The proximity operators of the ℓ0 and ℓ1 norms are the well-known hard- and soft-thresholding estimators, respectively. In this study, the authors give a complete study on the properties of th...
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In this study, a non-linear filtering algorithm for state estimation with symmetric alpha-stable (SαS) noise is presented. The dynamic system model investigated here can be described by a linear state-space equation and a non-linear observation equation. The contribution of this study can be summarised as follows. First, particle filtering approach is employed for coarse estimation of the u...
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Signal reconstruction from non-uniform samples, especially for non-stationary signals, is an important issue in the area of digital signal processing. As a type of signal processing tool, the fractional Fourier transform has been proved to be effective for solving problems in non-stationary signal processing. For non-stationary discrete-time signals, the reconstruction of uniformly sampled signals...
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In this paper, the authors address the tasks of audio source counting and separation for two-channel instantaneous mixtures. This goal is achieved in two steps. First, a novel scheme is proposed for estimating the number of sources and the corresponding channel intensity difference (CID) values. For this purpose, an angular spectrum is evaluated as a function of the ratio of the magnitude spectrog...
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In compressive sensing (CS)-based spectrum sensing literature, most studies consider accurate reconstruction of the primary user signal rather than detection of the signal. Furthermore, possible absence of the signal is not taken into account while evaluating the spectrum sensing performance. In this study, Bayesian CS is studied in detail for primary user detection. In addition to assessing the s...
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As a data-driven, equation-free decomposition method, the DMD can characterise dynamic behaviour of a non-linear system by using the DMD modes and eigenvalues. However, all current provable algorithms suffer from a separate procedure for obtaining the DMD modes and determining the number of modes. In this study, the authors propose a nuclear norm regularised DMD (NNR-DMD) algorithm that produces l...
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The authors propose a robust artificial bandwidth extension (ABE) technique to improve narrowband (NB) speech signal quality using an enhanced spectrum envelope and excitation estimation. For envelope estimation, they propose an enhanced envelope estimation method using a deep neural network with multiple layers. For excitation estimation, they use a whitened NB excitation signal that is generated...
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Dynamic estimation in signal processing and target tracking often involves non-linear models. These non-linear models are usually linearised through the first-order Taylor approximation in estimation process. However, the error generated by the first-order Taylor approximation is not negligible when the non-linearity of a model is high or the input error is large. This study proposes a new lineari...
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New block formulations for an active noise control (ANC) system using only convolution machines are presented. The proposed approaches are different from conventional block least-mean-square (LMS) algorithms that use both convolution and cross-correlation machines. The block implementation is also applied to the filtering of the reference signal by the secondary-path estimate. In addition to the u...
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In cognitive radio, there might be some information about primary users' signals available at secondary users' receivers since communications systems usually employ training signals for channel estimation and synchronization purposes. This training information can be exploited along with data symbols to perform semi-blind detection of primary users' signals. In the literature, it is considered tha...
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The authors develop methods for the time-frequency (TF) analysis of human gait radar signals. In particular the authors demonstrate how knowledge of different motion classes can be obtained via a Markov chain model of state transitions based on the TF envelope structure associated with the motion sequence being analysed. The class-conditional knowledge thus obtained allows us to effectively extrac...
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This study considers the phase noise filtering problem for interferometric phase image using sparse optimisation technique. Since the original model can be formulated as a rank minimisation problem, it is difficult to solve. One appealing approach is to use a nuclear norm (NN) regularisation to relax the rank regulariser. However, the performance of such approach is not satisfying. In this study, ...
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Several new results about Zak transform and uncertainty principles in the linear canonical transform (LCT) domains are presented. The results obtained rely mainly on relationship between the LCT and the classical Fourier transform. The findings will likely have potential applications in optics and signal processing.
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This study investigates state estimation problem for systems with delayed measurements, which is often encountered in networked control systems. The measurement transmission delay is modelled as Markov chain. By using the state augmentation technique, the system with delayed measurements is converted into a special multiple model system, then the interacting multiple model algorithm is applied to ...
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The integrity of the electric power cables is vital to the safety of an entire electrical system. To ensure the health of the cables, a technique is needed for both detecting/locating defects, and predicting hard defects before they occur. The theory and limitations of the classical wiring diagnostic techniques time domain reflectometry (TDR) and frequency domain reflectometry (FDR) are discussed....
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This study is concerned with the problem of robust reliable dissipative fllter design for networked control systems (NCSs) with sensor failures and random packet dropouts. The considered NCS model is subject to the sources of uncertainty in the system parameters. The sensor signals are modelled by sequences of a Bernoulli distributed white sequence and the packet dropouts may occur randomly during...
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This study deals with the problem of robust H∞ finite-time boundedness analysis and design of finite-time H∞ feedback control for discrete switched systems. By using sojourn probability information, a new kind of switched system model is proposed. Based on this model, sufficient conditions for the H∞ finite-time boundedness...
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